diff --git a/src/fhda/notebook_env.py b/src/fhda/notebook_env.py
index ee02ec2..081ee30 100644
--- a/src/fhda/notebook_env.py
+++ b/src/fhda/notebook_env.py
@@ -141,7 +141,7 @@ def __init__(
                 directories from the aviary-storage GCS bucket. Should only be enabled if the
                 task requires data on GCS. Disabled by default.
             run_notebook_on_edit: If True (default), the whole notebook will be rerun
-                after each edit. If False, only a the cell that was edited will be rerun.
+                after each edit. If False, only the cell that was edited will be rerun.
         """
         self.work_dir = Path(work_dir)
         self.nb_path = Path(nb_path) if nb_path else self.work_dir / self.NOTEBOOK_NAME
diff --git a/src/fhda/utils.py b/src/fhda/utils.py
index b7ea77e..f06f3e6 100644
--- a/src/fhda/utils.py
+++ b/src/fhda/utils.py
@@ -32,6 +32,25 @@
 }
 
 
+def configure_logging():
+    """Configure logging for the application."""
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+    )
+
+    loggers_config = {
+        "LiteLLM": logging.WARNING,
+        "LiteLLM Router": logging.WARNING,
+        "LiteLLM Proxy": logging.WARNING,
+        "httpx": logging.WARNING,
+        "httpcore.http11": logging.WARNING,
+    }
+
+    for logger_name, level in loggers_config.items():
+        logging.getLogger(logger_name).setLevel(level)
+
+
 class NBLanguage(StrEnum):
     PYTHON = auto()
     R = auto()
diff --git a/src/scripts/platform_eval.py b/src/scripts/platform_eval.py
index 50e4f4c..6a6096a 100644
--- a/src/scripts/platform_eval.py
+++ b/src/scripts/platform_eval.py
@@ -7,8 +7,8 @@
 import pandas as pd
 import logging
 from pathlib import Path
-from crow_client import CrowClient, JobResponseVerbose
-from crow_client.models import AuthType, Stage
+from futurehouse_client import FutureHouseClient, JobResponseVerbose
+from futurehouse_client.models import AuthType, Stage
 from aviary.utils import MultipleChoiceQuestion, eval_answer, EvalAnswerMode
 
 
@@ -33,9 +33,9 @@ def create_client(
     api_key: Optional[str] = None,
     stage: Stage = getattr(Stage, ENV),
     organization: str = "FutureHouse",
-) -> CrowClient:
-    """Create and return a CrowClient instance."""
-    return CrowClient(
+) -> FutureHouseClient:
+    """Create and return a FutureHouseClient instance."""
+    return FutureHouseClient(
         stage=stage,
         organization=organization,
         auth_type=AuthType.API_KEY,
@@ -64,12 +64,12 @@ def load_job_data(file_path: Union[str, Path]) -> List[Dict[str, Any]]:
 
 
 async def fetch_jobs_batch(
-    client: CrowClient, job_ids: List[str], batch_size: int = 10
+    client: FutureHouseClient, job_ids: List[str], batch_size: int = 10
 ) -> List[Dict[str, Any]]:
     """Fetch jobs in batches to avoid memory issues.
 
     Args:
-        client: CrowClient instance
+        client: FutureHouseClient instance
         job_ids: List of job IDs to fetch
         batch_size: Number of jobs to fetch in each batch
 
diff --git a/src/scripts/platform_run_jobs.py b/src/scripts/platform_run_jobs.py
index 364b72d..b7ebca1 100644
--- a/src/scripts/platform_run_jobs.py
+++ b/src/scripts/platform_run_jobs.py
@@ -9,9 +9,9 @@
 import datasets
 from ldp.agent import AgentConfig
 from aviary.core import MultipleChoiceQuestion
-from crow_client import CrowClient
-from crow_client.models import Stage, JobRequest, RuntimeConfig
-from crow_client.models.app import AuthType
+from futurehouse_client import FutureHouseClient
+from futurehouse_client.models import Stage, JobRequest, RuntimeConfig
+from futurehouse_client.models.app import AuthType
 import src.fhda.prompts as prompts
 
 logger = logging.getLogger(__name__)
@@ -187,7 +187,7 @@ async def submit_jobs(
         The answer string from the agent
     """
 
-    client = CrowClient(
+    client = FutureHouseClient(
         stage=CROW_STAGE,
         auth_type=AuthType.API_KEY,
         api_key=API_KEY,